Researchers at the U.S. National Institutes of Health (NIH) have applied artificial intelligence (AI) to improve next-generation imaging of cells in the back of the eye, NIH said on Wednesday.

With AI, imaging is 100 times faster and improves image contrast 3.5-fold, according to the researchers.

The advance will provide researchers with a better tool to evaluate age-related macular degeneration and other retinal diseases, they said.

"Artificial intelligence helps overcome a key limitation of imaging cells in the retina, which is time," said Johnny Tam, who leads the Clinical and Translational Imaging Section at NIH's National Eye Institute.

Tam is developing a technology called adaptive optics (AO) to improve imaging devices based on optical coherence tomography (OCT). Like ultrasound, OCT is noninvasive, quick, painless, and standard equipment in most eye clinics.

Tam and his team developed a novel AI-based method called parallel discriminator generative adverbial network (P-GAN) – a deep learning algorithm.

By feeding the P-GAN network nearly 6,000 manually analyzed AO-OCT-acquired images of human retinal pigment epithelium, a layer of tissue behind the light-sensing retina, each paired with its corresponding speckled original, the team trained the network to identify and recover speckle-obscured cellular features.